A new colorectal cancer risk prediction model incorporating family history, personal and environmental factors
Aung Ko Win,
Robert J. MacInnis,
Loic Le Marchand,
Noralane M. Lindor,
John A. Baron,
John L Hopper,
James G. Dowty,
Antonis C. Antoniou,
Mark A. Jenkins,
Polly A. Newcomb
Posted 07 Jun 2019
bioRxiv DOI: 10.1101/662106
Posted 07 Jun 2019
Purpose: Reducing colorectal cancer (CRC) incidence and mortality through early detection would improve efficacy if targeted. A CRC risk-prediction model incorporating personal, family, genetic and environmental risk factors could enhance prediction. Methods: We developed risk-prediction models using population-based CRC cases (N=4,445) and controls (N=3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). A familial risk profile (FRP) was calculated to summarize individuals risk based on their CRC family history, family structure, germline mutation probability in major susceptibility genes, and a polygenic component. Using logistic regression, we developed risk models including individuals FRP or a binary CRC family-history (FH), and risk factors collected at recruitment. Model validation used follow-up data for population- (N=12,052) and clinic-based (N=5,584) relatives with no cancer history at recruitment, assessing calibration (E/O) and discrimination (AUC). Results: The E/O (95% confidence interval [CI]) for FRP models for population-based relatives were 1.04 (0.74-1.45) and 0.86 (0.64-1.20) for men and women, and for clinic-based relatives 1.15 (0.87-1.58) and 1.04 (0.76-1.45). The age-adjusted AUC (95% CI) for FRP models in population-based relatives were 0.69 (0.60-0.78) and 0.70 (0.62-0.77), and for clinic-based relatives 0.77 (0.69-0.84) and 0.68 (0.60-0.76). The incremental values of AUC (95% CI) for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) and 0.10 (0.04-0.16), and for clinic-based relatives 0.11 (0.05-0.17) and 0.11 (0.06-0.17). Conclusion: The FRP-based model and FH-based model calibrate well in both settings. The FRP-based model provided better risk-prediction and discrimination than the FH-based model. A detailed family history may be useful for targeted risk-based screening and clinical management.
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